Bitcoin: How can I effectively trace code paths for fuzz testing in a Bitcoin core?

Tracing Code Paths for Fuzz Testing in Bitcoin Core

Fuzz Testing, which involves intentionally introducing errors or unexpected inputs into software systems to test their robustness and resilience, can be particularly challenging when Dealing with Complex Codebases Like Bitcoin’s Core. When it comes to tracing the source of function calls during fuzz testing, navigating through the code can be frustrating, especially for developers without extensive familiarity with the underlying architecture.

Understanding Bitcoin Core’s Execution Model

Before diving into tracing code paths, let’s quickly understand how Bitcoin core executes functions. The net_processing.cpp file is a critical component that performs various network-related tasks, such as packet processing, transaction verification, and consensus protocol execution. When executing this function, the CPU may perform a sequence of instructions, which can be difficult to follow due to the nature of modern CPUs.

Fuzz Testing Frameworks

To aid in tracing code paths during fuzz testing, severe frameworks have been developed:

* AddressSanitizer : A highly optimized and efficient sanitizer for c/c ++ that provides detailed information about memory accesses and function calls.

* Valgrind : A memory debugging tool for detecting leaks, crashes, and other memory-related issues. It also includes a set of tools for fuzz testing.

* GCC’s built-in Strace command

: this command allows you to execute system calls and inspecting their argument.

Using Strace With Fuzz Testing

When using Strace, it’s essential to start from the beginning of your fuzz test function, as each call will be traced separately. To do this:

• Compile your Bitcoin Core Code Into An Object File (Obj) and A Shared Library (Libcore).

• Use Valgrind withGCC (or its equivalent for other compilers) to generate a binary that includes the Strace Command:

`Bash

GCC -Std = C99 -Wall -WEXTRA -Coverage -Fsanitize = address obj/core.c -o core

valgrind-leak-check = full-show-leak-kinds = all–Sroot =/USR-Follow-Syms = Core ./core

`

• Run The Generated Binary With Fuzz To Start Your Fuzz Test:

`Bash

./core

`

Fuzz Testing Example

To Demonstrate how you can use Strace for Tracing Code Paths, let’s create a simple example that generates a random number and checks if it matches a value:

`C

#include

uint32_t generaterandom (uint8_t* buffer) {

uint32_ generated;

do {

generated = rand ();

} while (generated == 0);

// introduce an error by modifying the input buffer

*(buffer + 1) = 42;

Return generated;

}

You are Main () {

Const size_t buffsize = 10;

Uint8_t buffer [buffsize];

uint32_ generated;

// generate a random number, but introduce an error in the process

generated = generaterandom (buffer);

// check if the expected value matches

assert (generated == 42 && memcmp (buffer, expected_value, buffsize) == 0);

Return 0;

}

`

Tracing Code Paths

With this example and a basic understanding of Strace USage, you can follow these steps to trace code paths:

• Compile the Generaterandom.c file into an object file (obj) and a shared library (Libcore).

• Use Valgrind withGCC (or its equivalent) to generate a binary that including the Strace Command:

`Bash

GCC -Std = C99 -Wall -WEXTRA -Coverage -Fsanitize = address obj/core.c -o core

valgrind-leak-check = full-show-leak-kinds = all–Sroot =/USR-Follow-Syms = Core ./core

`

• Run The Generated Binary With Fuzz To Start Your Fuzz Test:

`Bash

./core

`

• Use the Strace command to inspect the function calls, focusing on the source of the error (i.e.

Ethereum Malleable Attack